Book description
Praise for the Second Edition
"As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available."
—Technometrics
This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement
The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods.
In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include:
Updated coverage of control charts, with newly added tools
The latest research on the monitoring of linear profiles and other types of profiles
Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures
New discussions on design of experiments that include conditional effects and fraction of design space plots
New material on Lean Six Sigma and Six Sigma programs and training
Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic.
Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.
Table of contents
- Cover Page
- Title Page
- Copyright
- Contents
- Preface
- Preface to the Second Edition
- Preface to the First Edition
- PART I: Fundamental Quality Improvement and Statistical Concepts
-
PART II: Control Charts and Process Capability
-
CHAPTER 4: Control Charts for Measurements With Subgrouping (for One Variable)
- 4.1 BASIC CONTROL CHART PRINCIPLES
- 4.2 REAL-TIME CONTROL CHARTING VERSUS ANALYSIS OF PAST DATA
- 4.3 CONTROL CHARTS: WHEN TO USE, WHERE TO USE, HOW MANY TO USE
- 4.4 BENEFITS FROM THE USE OF CONTROL CHARTS
- 4.5 RATIONAL SUBGROUPS
- 4.6 BASIC STATISTICAL ASPECTS OF CONTROL CHARTS
- 4.7 ILLUSTRATIVE EXAMPLE
- 4.8 ILLUSTRATIVE EXAMPLE WITH REAL DATA
- 4.9 DETERMINING THE POINT OF A PARAMETER CHANGE
- 4.10 ACCEPTANCE SAMPLING AND ACCEPTANCE CONTROL CHART
- 4.11 MODIFIED LIMITS
- 4.12 DIFFERENCE CONTROL CHARTS
- 4.13 OTHER CHARTS
- 4.14 AVERAGE RUN LENGTH (ARL)
- 4.15 DETERMINING THE SUBGROUP SIZE
- 4.16 OUT-OF-CONTROL ACTION PLANS
- 4.17 ASSUMPTIONS FOR THE CHARTS IN THIS CHAPTER
- 4.18 MEASUREMENT ERROR
- 4.19 SOFTWARE
- 4.20 SUMMARY
- APPENDIX
- REFERENCES
- EXERCISES
- CHAPTER 5: Control Charts for Measurements Without Subgrouping (for One Variable)
- CHAPTER 6: Control Charts for Attributes
-
CHAPTER 7: Process Capability
- 7.1 DATA ACQUISITION FOR CAPABILITY INDICES
- 7.2 PROCESS CAPABILITY INDICES
- 7.3 ESTIMATING THE PARAMETERS IN PROCESS CAPABILITY INDICES
- 7.4 DISTRIBUTIONAL ASSUMPTION FOR CAPABILITY INDICES
- 7.5 CONFIDENCE INTERVALS FOR PROCESS CAPABILITY INDICES
- 7.6 ASYMMETRIC BILATERAL TOLERANCES
- 7.7 CAPABILITY INDICES THAT ARE A FUNCTION OF PERCENT NONCONFORMING
- 7.8 MODIFIED k INDEX
- 7.9 OTHER APPROACHES
- 7.10 PROCESS CAPABILITY PLOTS
- 7.11 PROCESS CAPABILITY INDICES VERSUS PROCESS PERFORMANCE INDICES
- 7.12 PROCESS CAPABILITY INDICES WITH AUTOCORRELATED DATA
- 7.13 SOFTWARE FOR PROCESS CAPABILITY INDICES
- 7.14 SUMMARY
- REFERENCES
- EXERCISES
-
CHAPTER 8: Alternatives to Shewhart Charts
- 8.1 INTRODUCTION
- 8.2 CUMULATIVE SUM PROCEDURES: PRINCIPLES AND HISTORICAL DEVELOPMENT
- 8.3 CUSUM PROCEDURES FOR CONTROLLING PROCESS VARIABILITY
- 8.4 APPLICATIONS OF CUSUM PROCEDURES
- 8.5 GENERALIZED LIKELIHOOD RATIO CHARTS: COMPETITIVE ALTERNATIVE TO CUSUM CHARTS
- 8.6 CUSUM PROCEDURES FOR NONCONFORMING UNITS
- 8.7 CUSUM PROCEDURES FOR NONCONFORMITY DATA
- 8.8 EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
- 8.9 SOFTWARE
- 8.10 SUMMARY
- REFERENCES
- EXERCISES
-
CHAPTER 9: Multivariate Control Charts for Measurement and Attribute Data
- 9.1 HOTELLING'S T2 DISTRIBUTION
- 9.2 A T2 CONTROL CHART
- 9.3 MULTIVARIATE CHART VERSUS INDIVIDUAL X-CHARTS
- 9.4 CHARTS FOR DETECTING VARIABILITY AND CORRELATION SHIFTS
- 9.5 CHARTS CONSTRUCTED USING INDIVIDUAL OBSERVATIONS
- 9.6 WHEN TO USE EACH CHART
- 9.7 ACTUAL ALPHA LEVELS FOR MULTIPLE POINTS
- 9.8 REQUISITE ASSUMPTIONS
- 9.9 EFFECTS OF PARAMETER ESTIMATION ON ARLs
- 9.10 DIMENSION-REDUCTION AND VARIABLE SELECTION TECHNIQUES
- 9.11 MULTIVARIATE CUSUM CHARTS
- 9.12 MULTIVARIATE EWMA CHARTS
- 9.13 EFFECT OF MEASUREMENT ERROR
- 9.14 APPLICATIONS OF MULTIVARIATE CHARTS
- 9.15 MULTIVARIATE PROCESS CAPABILITY INDICES
- 9.16 SUMMARY
- APPENDIX
- REFERENCES
- EXERCISES
-
CHAPTER 10: Miscellaneous Control Chart Topics
- 10.1 PRE-CONTROL
- 10.2 SHORT-RUN SPC
- 10.3 CHARTS FOR AUTOCORRELATED DATA
- 10.4 CHARTS FOR BATCH PROCESSES
- 10.5 CHARTS FOR MULTIPLE-STREAM PROCESSES
- 10.6 NONPARAMETRIC CONTROL CHARTS
- 10.7 BAYESIAN CONTROL CHART METHODS
- 10.8 CONTROL CHARTS FOR VARIANCE COMPONENTS
- 10.9 CONTROL CHARTS FOR HIGHLY CENSORED DATA
- 10.10 NEURAL NETWORKS
- 10.11 ECONOMIC DESIGN OF CONTROL CHARTS
- 10.12 CHARTS WITH VARIABLE SAMPLE SIZE AND/OR VARIABLE SAMPLING INTERVAL
- 10.13 USERS OF CONTROL CHARTS
- 10.14 SOFTWARE FOR CONTROL CHARTING
- BIBLIOGRAPHY
- EXERCISES
-
CHAPTER 4: Control Charts for Measurements With Subgrouping (for One Variable)
-
PART III: Beyond Control Charts: Graphical and Statistical Methods
- CHAPTER 11: Graphical Methods
-
CHAPTER 12: Linear Regression
- 12.1 SIMPLE LINEAR REGRESSION
- 12.2 WORTH OF THE PREDICTION EQUATION
- 12.3 ASSUMPTIONS
- 12.4 CHECKING ASSUMPTIONS THROUGH RESIDUAL PLOTS
- 12.5 CONFIDENCE INTERVALS AND HYPOTHESIS TEST
- 12.6 PREDICTION INTERVAL FOR Y
- 12.7 REGRESSION CONTROL CHART
- 12.8 CAUSE-SELECTING CONTROL CHARTS
- 12.9 LINEAR, NONLINEAR, AND NONPARAMETRIC PROFILES
- 12.10 INVERSE REGRESSION
- 12.11 MULTIPLE LINEAR REGRESSION
- 12.12 ISSUES IN MULTIPLE REGRESSION
- 12.13 SOFTWARE FOR REGRESSION
- 12.14 SUMMARY
- REFERENCES
- EXERCISES
-
CHAPTER 13: Design of Experiments
- 13.1 A SIMPLE EXAMPLE OF EXPERIMENTAL DESIGN PRINCIPLES
- 13.2 PRINCIPLES OF EXPERIMENTAL DESIGN
- 13.3 STATISTICAL CONCEPTS IN EXPERIMENTAL DESIGN
- 13.4 t-TESTS
- 13.5 ANALYSIS OF VARIANCE FOR ONE FACTOR
- 13.6 REGRESSION ANALYSIS OF DATA FROM DESIGNED EXPERIMENTS
- 13.7 ANOVA FOR TWO FACTORS
- 13.8 THE 23 DESIGN
- 13.9 ASSESSMENT OF EFFECTS WITHOUT A RESIDUAL TERM
- 13.10 RESIDUAL PLOT
- 13.11 SEPARATE ANALYSES USING DESIGN UNITS AND UNCODED UNITS
- 13.12 TWO-LEVEL DESIGNS WITH MORE THAN THREE FACTORS
- 13.13 THREE-LEVEL FACTORIAL DESIGNS
- 13.14 MIXED FACTORIALS
- 13.15 FRACTIONAL FACTORIALS
- 13.16 OTHER TOPICS IN EXPERIMENTAL DESIGN AND THEIR APPLICATIONS
- 13.17 SUMMARY
- REFERENCES
- EXERCISES
-
CHAPTER 14: Contributions of Genichi Taguchi and Alternative Approaches
- 14.1 “TAGUCHI METHODS”
- 14.2 QUALITY ENGINEERING
- 14.3 LOSS FUNCTIONS
- 14.4 DISTRIBUTION NOT CENTERED AT THE TARGET
- 14.5 LOSS FUNCTIONS AND SPECIFICATION LIMITS
- 14.6 ASYMMETRIC LOSS FUNCTIONS
- 14.7 SIGNAL-TO-NOISE RATIOS AND ALTERNATIVES
- 14.8 EXPERIMENTAL DESIGNS FOR STAGE ONE
- 14.9 TAGUCHI METHODS OF DESIGN
- 14.10 DETERMINING OPTIMUM CONDITIONS
- 14.11 SUMMARY
- REFERENCES
- EXERCISES
- CHAPTER 15: Evolutionary Operation
- CHAPTER 16: Analysis of Means
- CHAPTER 17: Using Combinations of Quality Improvement Tools
- Answers to Selected Exercises
- APPENDIX: Statistical Tables
- Author Index
- Subject Index
Product information
- Title: Statistical Methods for Quality Improvement, Third Edition
- Author(s):
- Release date: August 2011
- Publisher(s): Wiley
- ISBN: 9780470590744
You might also like
book
Statistical Quality Control, 7th Edition
The Seventh Edition of Introduction to Statistical Quality Control provides a comprehensive treatment of the major …
book
Statistical Process Control for Managers, Second Edition
If you have been frustrated by very technical statistical process control (SPC) training materials, then this …
book
Douglas Montgomery's Introduction to Statistical Quality Control
Master Statistical Quality Control using JMP ! Using examples from the popular textbook by Douglas Montgomery, …
book
Building Quality Management Systems
Current and emerging trends in the domains of health management and the work sector, the abundance …